ISSN:
1365-2109
Source:
Blackwell Publishing Journal Backfiles 1879-2005
Topics:
Agriculture, Forestry, Horticulture, Fishery, Domestic Science, Nutrition
Notes:
Abstract. A simplified mass balance model was used to predict spatially averaged nitrogen and chlorophyll concentrations in Big Glory Bay, Stewart Island, New Zealand. The bay is used for salmon fanning and during January 1989 supported a dense bloom of Heterosigma alcashiwo which killed 600t of fish. Nutrient concentrations in the bay arc affected by inputs from bottom sediments, catchment run-off, rainfall, salmon farms and water exchange with Paterson Inlet (into which Big Glory Bay drains). The nitrogen model was calibrated using field data collected on 11–27 February 1988 and successfully predicted the mean nitrogen concentration of the bay during the 1989 bloom. Nitrogen concentrations in the bay were most affected by the nitrogen concentration in Paterson Inlet, which appears to vary year-to-year as a result of the incursion into Fouveaux Strait of highly fertile oceanic water. The marginal effect of the salmon farms was to increase the mean nitrogen concentration of Big Glory Bay by about 30%. The nitrogen model was combined with a logistic phytoplankton growth model to examine the effects of nitrogen availability and hydraulic flushing on phytoplankton yields (measured as chlorophyll a). The spatially averaged chlorophyll concentration of Big Glory Bay was reliably predicted during the 1989 study, when there was strong evidence that phytoplankton were nitrogen limited. The model indicated that nitrogen inputs from the salmon farms increased the mean chlorophyll concentration of the bay by about 33%. The model was less successful in predicting chlorophyll concentrations in February 1988 when phytoplankton growth was not restricted by nitrogen, but may have been controlled by zooplankton grazing or sedimentation (which were not included in the model). The use of mo re complex three-dimensional models is advocated to describe the observed‘patchiness’in Heterosigma distribution.
Type of Medium:
Electronic Resource
URL:
http://dx.doi.org/10.1111/j.1365-2109.1992.tb00797.x
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